Over the past few years, context learning has played an important role in the sub-tasks of person search, i.e., object detection [1]}, [2]}, [3]} and person re-ID [4]}, [5]}. In object detection, context information often plays a role in reasoning and help establish the relationship between objects and rationality. Among most of the existing approaches, the context used can be divided into two categories: global scene context and local group context.
With global scene context, the relationship between the scene and target object can be established. For instance, a beach often involves a boat, and an umbrella often appears in a rainy day. To be short, more information in the background could be absorbed to assist the localization on target objects. For instance, in [2]}, scene context is applied to enhance some parts of object state, which may help find the neglected small objects. In [3]}, Chen et al. used a correlation estimation procedure to select useful contextual information from the surrounding regions, which improves the quality of their detection results.
